Community

Dawn Parker Member since: Monday, October 24, 2011 Full Member Reviewer

PhD, Agricultural and Resource Economics, UC Davis

Dr. Dawn Parker is a professor at the University of Waterloo in the School of Planning. Her research focuses on the development of integrated socio-economic and biophysical models of land-use change. Dr. Parker works with agent-based modeling, complexity theory, geographic information systems, and environmental and resource economics. Her current ongoing projects include Waterloo Area Regional Model (WARM) Urban intensification vs. suburban flight, a SSHRC funded development grant that explores the causal relationships between light rail transit and core-area intensification, and the Digging into Data MIRACLE (Mining relationships among variables in large datasets from complex systems) project.

Nilda Eliquen Member since: Sunday, July 19, 2009 Full Member Reviewer

MS COMPUTER SCIENCE, BS CHEMICAL ENGINEERING

Social Computing particularly on data mining tweets, blogs, social networking sites for disaster events.

Mirsad Hadzikadic Member since: Thursday, January 12, 2012 Full Member Reviewer

PhD Computer Science, SMU, MPA, Harvard University

Complex adaptive systems, complexity, systems science, creativity, data mining, machine learning, economic and health systems, science education

Andrew Gillreath-Brown Member since: Thursday, July 25, 2019 Full Member

A.S., Pre-Engineering, Wallace State Community College, B.S., Mathematics and Natural Sciences, Freed-Hardeman University, B.A., Religious Studies, Freed-Hardeman University, B.A., Anthropology, Middle Tennessee State University, M.S., Applied Geography: Environmental Archaeology, University of North Texas

I am a computational archaeologist interested in how individuals and groups respond to both large scale processes such as climate change and local processes such as violence and wealth inequality. I am currently a PhD Candidate in the Department of Anthropology at Washington State University.

My dissertation research focuses on experimenting with paleoecological data (e.g., pollen) to assess whether or not different approaches are feasible for paleoclimatic field reconstructions. In addition, I will also use pollen data to generate vegetation (biome) reconstructions. By using tree-ring and pollen data, we can gain a better understanding of the paleoclimate and the spatial distribution of vegetation communities and how those changed over time. These data can be used to better understand changes in demography and how people responded to environmental change.

In Summer 2019, I attended the Santa Fe Institute‘s Complex Systems Summer School, where I got to work in a highly collaborative and interdisciplinary international scientific community. For one of my projects, I got to merry my love of Sci-fi with complexity and agent-based modeling. Sci-fi agent-based modeling is an anthology and we wanted to build a community of collaborators for exploring sci-fi worlds. We also have an Instagram page (@Scifiabm).

Sedar Olmez Member since: Wednesday, November 06, 2019 Full Member

MSci in Computer Science, MSc in Data Analytics and Society

Sedar is a PhD student at the University of Leeds, department of Geography. He graduated in Computer Science at King’s College London 2018. From a very early stage of his degree, he focused on artificial intelligence planning implementations on drones in a search and rescue domain, and this was his first formal attempt to study artificial intelligence. He participated in summer school at Boğaziçi University in Istanbul working on programming techniques to reduce execution time. During his final year, he concentrated on how argumentation theory with natural language processing can be used to optimise political influence. In the midst of completing his degree, he applied to Professor Alison Heppenstall’s research proposal focusing on data analytics and society, a joint endeavour with the Alan Turing Institute and the Economic and Social Research Council. From 2018 - 2023 he will be working on his PhD at the Alan Turing Institute and Leeds Institute for Data Analytics.

Sedar will be focusing on data analytics and smart cities, developing a programming library to try simulate how policies can impact a small world of autonomous intelligent agents to try deduce positive or negative impact in the long run. If the impact is positive and this is conveyed collectively taking into consideration the agent’s health, happiness and other social characteristics then the policy can be considered. Furthermore, he will work on agent based modelling to solve and provide faster solutions to economic and social elements of society, establishing applied and theoretical answers. Some other interests are:

  • Multi-agent systems
  • Intelligent agents
  • Natural language processing
  • Artificial intelligence planning
  • Machine learning
  • Neural networks
  • Genetic programming
  • Geocomputation
  • Argumentation theory
  • Smart cities

Alex Kara Member since: Wednesday, April 10, 2013

BA in Archaeology, Boston University, 2012

I am interested in using agent based modelling and systematic data collection to understand diachronic human-environment interactions in the Maya region of Guatemala, Mexico, and Belize.

Robert Axtell Member since: Thursday, July 14, 2016

Ph.D.

Agent-based computing in economics and finance
Large-scale agent-based models
Agent models calibrated by micro-data
Complex adaptive systems
Mathematical analysis of agent systems

Rory Sie Member since: Tuesday, February 11, 2014

dr., MSc.

Mainly interested in studying social networks of learners, teachers, and innovators. Uses Social Network Analysis, but also sentiment analysis, data mining, and recommender system techniques.

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